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Bibliographic Details
Main Author: Gao, Eric
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.10340
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author Gao, Eric
author_facet Gao, Eric
contents I study how a startup with uncertainty over product quality and no knowledge of the underlying diffusion network optimally chooses initial seeds. To ensure widespread adoption when the product is good while minimizing negative perceptions when it is bad, the optimal number of initial seeds should grow logarithmically with network size. When there are agents of different types that govern their connectivity, it is asymptotically optimal to seed agents of a single type: the type that minimizes the marginal cost per probability of making the product go viral. These results rationalize startup behavior in practice.
format Preprint
id arxiv_https___arxiv_org_abs_2506_10340
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Seeding an Uncertain Technology
Gao, Eric
Theoretical Economics
I study how a startup with uncertainty over product quality and no knowledge of the underlying diffusion network optimally chooses initial seeds. To ensure widespread adoption when the product is good while minimizing negative perceptions when it is bad, the optimal number of initial seeds should grow logarithmically with network size. When there are agents of different types that govern their connectivity, it is asymptotically optimal to seed agents of a single type: the type that minimizes the marginal cost per probability of making the product go viral. These results rationalize startup behavior in practice.
title Seeding an Uncertain Technology
topic Theoretical Economics
url https://arxiv.org/abs/2506.10340